Newspaper Articles Related to the Not Criminally Responsible on Account of Mental Disorder (NCRMD) Designation: A Comparative Analysis
Bibliographic record
Abstract
OBJECTIVE: The not criminally responsible on account of mental disorder (NCRMD) designation remains widely misunderstood by the public. Such misunderstandings may also be reflected in the media. As such, the aim of this study is to conduct a preliminary examination of the tone and content of recent Canadian newspaper articles where NCRMD is a major theme, comparing these to generic articles about mental illness. METHODS: Articles about mental illness were gathered from major Canadian newspapers. These were then divided into two categories: 1) articles where NCRMD was a major theme and 2) articles where NCRMD was not a major theme. Articles were then coded for the presence or absence of 1) a negative tone, 2) stigmatising tone/content, 3) recovery/rehabilitation as a theme, and 4) shortage of resources/poor quality of care as a theme. RESULTS: The retrieval strategy resulted in 940 articles. Fourteen percent ( n = 131) of all articles had NCRMD as a major theme. In comparison to generic articles about mental illness, articles with NCRMD as a major theme were significantly more likely to have a negative tone ( P < 0.001) and stigmatising tone/content ( P < 0.001) and significantly less likely to have recovery/rehabilitation ( P < 0.001) or shortage of resources/poor quality of care as a theme ( P < 0.001). CONCLUSIONS: Articles with NCRMD as a theme were overwhelmingly negative and almost never focused on recovery or rehabilitation, in stark comparison to generic articles about mental illness.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.018 | 0.021 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".